Results 131 to 140 of about 6,522,305 (296)

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Trends in quantum reinforcement learning: State-of-the-arts and the road ahead

ETRI Journal
This paper presents the basic quantum reinforcement learning theory and its applications to various engineering problems. With the advances in quantum computing and deep learning technologies, various research works have focused on quantum deep learning ...
Soohyun Park, Joongheon Kim
doaj   +1 more source

Automation and Feature Selection Enhancement with Reinforcement Learning (RL)

CoRR
Effective feature selection, representation and transformation are principal steps in machine learning to improve prediction accuracy, model generalization and computational efficiency. Reinforcement learning provides a new perspective towards balanced exploration of optimal feature subset using multi-agent and single-agent models.
openaire   +3 more sources

The Collective Power of Bacteria as a Blueprint for Emergent Intelligence

Advanced Intelligent Systems, EarlyView.
Small cells, powerful collectives. Bacteria demonstrate how sophisticated behaviors can emerge from many simple individuals working together. We explore the remarkable world of bacterial communities and the mechanisms that underpin their complex emergent behaviors, enabling impressive adaptability, robustness, and responsiveness to changing ...
Johanna A. Blee, Thomas E. Gorochowski, Sabine Hauert   +2 more
wiley   +1 more source

Proximal policy optimization-based reinforcement learning approach for DC-DC boost converter control: A comparative evaluation against traditional control techniques

Heliyon
This article proposes a proximal policy optimization (PPO)-based reinforcement learning (RL) approach for DC-DC boost converter control that is compared with traditional control methods.
Utsab Saha, Atik Jawad, Shakib Shahria, A.B.M Harun-Ur Rashid   +3 more
doaj   +1 more source

Cold-RL: Learning Cache Eviction with Offline Reinforcement Learning for NGINX

CoRR
8 pages, 4 figures (system architecture, eviction path, training pipeline, and DQN algorithm), 2 tables.
Aayush Gupta, Arpit Bhayani
openaire   +3 more sources

Reinforcement Learning With a Low‐Cost Parallel Linkage Gripper for Static and Dynamic Planar In‐Hand Manipulation

Advanced Intelligent Systems, EarlyView.
Hardware‐learning co‐design combines volar‐plate‐inspired passive‐joint constraints with mechanism‐aware reinforcement learning for a low‐cost parallel‐linkage gripper. The resulting system performs quasi‐static object adjustment and dynamic pinch grasping, demonstrating reliable planar in‐hand manipulation and successful sim‐to‐real transfer. Parallel
Yanzhou Jin, Adam J. Spiers, Yusuke Iwasawa, Yutaka Matsuo, Yaonan Zhu   +4 more
wiley   +1 more source

Dual process impairments in reinforcement learning and working memory systems underlie learning deficits in physiological anxiety.

PLoS Computational Biology
Anxiety has been robustly linked to deficits in frontal executive function including working memory (WM) and attentional control processes. However, although anxiety has also been associated with impaired performance on learning tasks, computational ...
Jennifer D Senta, Sonia J Bishop, Anne G E Collins   +2 more
doaj   +1 more source

Interbody Wire for Reconfigurable Robots: Bridging Integrated Morphological Reconfiguration and Distributed Wire‐Mediated Cooperation

Advanced Intelligent Systems, EarlyView.
TwinX shows how a single interbody wire connecting two robots can support both integrated morphological reconfiguration and distributed wire‐mediated cooperation. When the robots dock, they reconfigure into different forms for locomotion and manipulation.
Shintaro Inoue, Kento Kawaharazuka, Keita Yoneda, Sota Yuzaki, Temma Suzuki, Kei Okada   +5 more
wiley   +1 more source

A Review of Reinforcement Learning for Fixed-Wing Aircraft Control Tasks

IEEE Access
Reinforcement learning (RL) has seen an uptick in research interest in recent years, with many papers published in a plethora of different fields, topics and applications. A lot of that can be attributed to the recent advancements in machine learning (ML)
David J. Richter, Ricardo A. Calix, Kyungbaek Kim   +2 more
doaj   +1 more source